Yoshimura Takaaki, Hasegawa Atsushi, Kogame Shoki, Magota Keiichi, Kimura Rina, Watanabe Shiro, Hirata Kenji, Sugimori Hiroyuki
Department of Health Sciences and Technology, Faculty of Health Sciences, Hokkaido University, Sapporo 060-0812, Japan.
Department of Medical Physics, Hokkaido University Hospital, Sapporo 060-8648, Japan.
Diagnostics (Basel). 2022 Mar 31;12(4):872. doi: 10.3390/diagnostics12040872.
In positron emission tomography (PET) imaging, image quality correlates with the injected [18F]-fluorodeoxyglucose (FDG) dose and acquisition time. If image quality improves from short-acquisition PET images via the super-resolution (SR) deep learning technique, it is possible to reduce the injected FDG dose. Therefore, the aim of this study was to clarify whether the SR deep learning technique could improve the image quality of the 50%-acquisition-time image to the level of that of the 100%-acquisition-time image. One-hundred-and-eight adult patients were enrolled in this retrospective observational study. The supervised data were divided into nine subsets for nested cross-validation. The mean peak signal-to-noise ratio and structural similarity in the SR-PET image were 31.3 dB and 0.931, respectively. The mean opinion scores of the 50% PET image, SR-PET image, and 100% PET image were 3.41, 3.96, and 4.23 for the lung level, 3.31, 3.80, and 4.27 for the liver level, and 3.08, 3.67, and 3.94 for the bowel level, respectively. Thus, the SR-PET image was more similar to the 100% PET image and subjectively improved the image quality, as compared to the 50% PET image. The use of the SR deep-learning technique can reduce the injected FDG dose and thus lower radiation exposure.
在正电子发射断层扫描（PET）成像中，图像质量与注入的[18F] - 氟脱氧葡萄糖（FDG）剂量及采集时间相关。如果通过超分辨率（SR）深度学习技术能从短采集时间的PET图像改善图像质量，那么就有可能降低FDG的注入剂量。因此，本研究的目的是阐明SR深度学习技术能否将50%采集时间图像的质量提高到100%采集时间图像的水平。108例成年患者纳入了这项回顾性观察研究。监督数据被分为9个子集用于嵌套交叉验证。SR - PET图像中的平均峰值信噪比和结构相似性分别为31.3 dB和0.931。50% PET图像、SR - PET图像和100% PET图像在肺水平的平均主观评分分别为3.41、3.96和4.23，在肝水平分别为3.31、3.80和4.27，在肠水平分别为3.08、3.67和3.94。因此，与50% PET图像相比，SR - PET图像与100% PET图像更相似，且主观上改善了图像质量。使用SR深度学习技术可降低FDG注入剂量，从而减少辐射暴露。
